Blood-vessel bloodstream simulation system, method therefor, and computer software program

ABSTRACT

This system is a system for analyzing blood flow which imposes a boundary condition relating to the blood flow to three dimensional shape data of a target vascular site of a subject and divides a lumen of the target vascular site into meshes for obtaining state quantities of the blood flow at each mesh position by means of computation, having: a labeling unit, by a computer, for reading out the three dimensional shape data on the lumen of the target vascular site, and labeling a plurality of vascular elements included in the target vascular based on a size of the cross-sectional area of each of the vascular elements; wherein, the computation of the state quantities is carried out by varying a level of mesh detail for each vascular element based on the labeling according to the size of the cross-sectional area.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a United States national phase of co-pendinginternational patent application No. PCT/JP2012/071626, filed Aug. 27,2012, which claims benefit of Japanese Patent Application No.2011-184751, filed Aug. 26, 2011, the disclosures of which areincorporated herein by reference.

FIELD OF THE INVENTION

The present invention relates to a system for simulating blood flow,method thereof, and computer software program.

BACKGROUND OF THE INVENTION

Cardiovascular diseases appear in various types of lesions includinganeurysm, atherosclerosis, and stenosis. These diseases are caused bypathological changes of normal parts with an influence of blood flow,and although the diseases would be fatal in many cases depending ontheir growth stages, it is extremely difficult to treat them becausesuch a treatment may risk the patient's life span. For understandingthese refractory cardiovascular diseases, it is beneficial to applyadvanced engineering technology including fluid analysis and structuralanalysis, in addition to the fundamental medical approach of studyingunderlying pathology.

For example, cerebral aneurysm is an angiopathy where a part of acerebral artery wall protrudes outward, forming a shape similar to aballoon, and there are an increasing number of clinical cases ofaccidentally discovering an un-ruptured aneurysm while conducting abrain image diagnosis. A cerebral aneurysm appears due to thevulnerability of the cerebral artery wall, altering a part of the wallto develop a lump which is fragile due to the lack of the tunica media,and it is most likely a cause of subarachnoid hemorrhage because manycases of cerebral aneurysm tend to appear in the subarachnoid space.Therefore, a cerebral aneurysm giving a high potential of rupture needsto be treated proactively by conducting a proper surgical treatment suchas a stent treatment.

However, the probability of the actual rupture of cerebral aneurysms isreported to be less than 1% annually for the size 10 mm or less; thus,considering the risk of post-surgical complication, preventive treatmentwould not be necessarily appropriate in some cases, and consequentlyrather than relying on surgical treatment alone, it is required todetermine a subject to be treated by judging an aneurysm at a greaterprobability of rupture. For this reason, there have been researchconducted on methods for diagnosing a cerebral aneurysm based on itssize and shape, the family record, the blood pressure, and the habit ofcigarette smoking, and other factors of the patient. Nevertheless, theseindicators are not deterministic factors of the diagnosis, anddeveloping a more effective diagnostic method is demanded.

Japanese Patent Application Publication No. 2010-207531 discloses MRIequipment that may diagnose the risk of aneurysmal rupture by analyzingthe viscous force of fluid that exerts on the inner wall of cerebralaneurysm, i.e., by analyzing the magnitude of wall shear stress of thefluid. However, regarding the correlation between the magnitude of thewall shear stress and the growth of aneurysm there are severalcontroversial arguments where the diagnostic results are contradictingeach other. A first theory is the High Wall Shear Stress (WSS) theorywhich explains that cerebral aneurysm grows due to an appearance of anendothelial cell fault once the wall shear stress exceeds a certainthreshold value which results in the infiltration of migratory cells,leading to reduce the mechanical strength of the aneurysm wall. A secondtheory is the Low WSS theory which explains that once the wall shearstress drops below a certain threshold value, platelets or white bloodcells that adhere to the endothelial cells lower the endothelialfunction, resulting in the reduction of the mechanical strength of theaneurysm wall. Because those theories have explanations opposite to eachother, the magnitude of the wall shear stress is not a direct measure ofdetermining the growth and rupture of the aneurysm.

There are other attempts to determine the rupturing risk byinvestigating the magnitude of the wall shear stress, e.g., a method foranalyzing the blood flow either experimentally or computationally toextract the wall shear stress from medical images acquired by MRI or CT.However, as pointed out above, there is no conclusive correlationbetween the magnitude of the wall shear stress and the risk of rupture,and furthermore, the method of using medical images medical image is amethodology that is only based on the morphology of a vascular lumen,and thus provides no interpretation of the flow itself. This is becausethe observation of medical images fails to allow us to obtainpathological information of cellular conditions and morphologicalinformation of aneurysmal wall thickness, which change locally on theaneurysm wall, while the magnitude of the wall shear stress itself alsovaries locally on the aneurysm wall.

Considering the above issues, the present invention has been researchedand developed, aiming the purpose that provides a method for determininga possible appearance of lesion in a target vascular site and itspotential growth based upon a diagnostic result of the blood flowcharacteristics of the targeted blood vessel, and furthermore, andpredicting the effect of treatment, a system thereof, and an accompaniedsoftware program.

SUMMARY OF THE INVENTION

In order to solve the above mentioned problem, according to the firstmain aspect of the present invention, there is provided a system foranalyzing blood flow which imposes a boundary condition relating to theblood flow to three dimensional data representing a shape of a targetvascular site of a subject and divides a lumen of the target vascularsite into meshes for obtaining state quantities of the blood flow ateach mesh position by means of computation, comprising:

a labeling unit, by a computer, for reading out the three dimensionaldata on the lumen of the target vascular site, and labeling a pluralityof vascular elements included in the target vascular based on a size ofa cross-sectional area of each of the vascular elements; wherein, thecomputation of the state quantities is carried out by varying a level ofmesh detail for each vascular element based on the labeling according tothe size of the cross-sectional area.

According to an embodiment of the present invention, the labeling unithas a storage unit, by a computer, for storing names of principal andother vascular elements contained in a specific target vascular site inconjunction with the specific target vascular site, and; a unit, by acomputer, for measuring cross-sectional area of each of vascularelements contained in a specific target vascular site in a plurality ofcross sections, identifying a blood vessel with a largest median valueof the area as a principal blood vessel as well as other vascularelements based on the determination of the principal blood vessel,labeling the names of the principal and other vascular elements, andthen outputting the labels together with the three-dimensional data.

In this case, the level of mesh detail is determined by a magnitude of amedian value of the cross-sectional area from a plurality of levels thatrange from coarse to fine.

According another embodiment, the system further comprises acomputational condition storage unit, by a computer, for storingmultiple sets of computational conditions including boundary conditionsto calculate state quantities of blood flow that flows through thethree-dimensional data, wherein the multiple sets of the computationalconditions contain one or more different computational condition valuesfor a calculation speed that a user requires, wherein the systemprovides a user with a list of possible computational speed, reads out aset of computational condition values relating to the selectedcomputational speed, calculates the blood flow state quantities based onthe computational condition values included in the selected set, andoutputs calculated results.

In this case, at least one set of the multiple sets of computationalcondition values preferably contains a computational condition valuewhich assumes a steady blood flow when a user requires a fastcalculation speed, and at least another set of the multiple sets of thecomputational condition values contains a computational condition valuewhich assumes a pulsatile blood flow when a user requires bettercalculation accuracy rather than calculation speed.

In addition, in this case, at least another set of computationalcondition values preferably contain a computational condition valueunder consideration of transition from a laminar flow to a turbulentflow within a pulsation cycle of the pulsatile blood flow.

Furthermore, this system preferably further has a first processor forcarrying out calculations for which a user requires more computationalspeed; a second processor for carrying out calculations for which a userrequires more computational accuracy; and a processor determination unitfor determining which processor to be used according to a choice made bya user. In this case, it is desirable that the second processor conductsparallel analyses by employing a plurality of high speed arithmeticoperation units. Furthermore, the second processor is preferablyinstalled in a separate location which is connectable with the systemthrough a communication network, and, when the processor determinationunit determines that the second processor is to be used, the processordetermination unit sends a part or all of the conditions required forcomputation to the second processor and receives calculation results viathe communication network.

According to yet another embodiment of the present invention, thissystem further comprises a surgical simulation unit, by a computer, forgenerating three-dimensional data representing a shape of the targetvascular site after a surgery by means of a simulation; wherein thesurgical simulation unit comprises: a treatment method receiving unit,by a computer, for displaying the three-dimensional data on a computerdisplay screen, and receiving a specification of a lesion on display anda selection of a surgical treatment method for the lesion; amodification method storage unit, by a computer, for pre-storingselectable treatment methods and methods for modifying thethree-dimensional data for respective treatment methods; and a modifiedthree-dimensional shape data output unit, by a computer, for reading outa modification method from the modification method storage unitaccording to the selection of a treatment method, modifying thethree-dimensional shape data related to the specification of the lesionby the selected method, and outputting the modified three-dimensionalshape data.

In this case, the selectable treatment methods preferably include coilembolization; wherein a method for modifying the three-dimensional datafor the coil embolization comprises a unit for placing a porousstructure on a part of the lumen of the target vascular site on thethree-dimensional data in order to simulate a state of blocking the partof the lumen of the target vascular site with the coil embolization. Inaddition, the system preferably further comprises a unit for adjusting acoil filling ratio with an aperture ratio of the porous structure.

In another example, the selectable treatment methods preferably includeclipping, wherein a method for modifying the three-dimensional data forthe clipping method comprises a unit for removing one or more polygonswhich configure a surface of a part of the vascular lumen (i.e., a partthat forms a lump), and a unit for regenerating the removed surface withone or more different polygons in order to simulate a state ofcompletely blocking the part of the vascular lumen.

Furthermore, the selectable treatment methods preferably include stentimplantation, wherein the method for modifying the three-dimensionaldata appropriate to this treatment method comprises a unit for modifyingan uneven surface on a part of the vascular lumen by moving ordistorting polygons in order to conduct a simulation of controllingblood flow in a blood vessel by applying a stent.

In addition, the selectable treatment methods preferably includeflow-diverting stent implantation, wherein the method for modifying thethree-dimensional data appropriate to this treatment method comprises aunit for defining a lattice structured object on the lumen of the targetvascular site on the three-dimensional data in order to conduct asimulation of restricting blood flow by implanting a flow-divertingstent. In this case, the system preferably has a unit for adjusting apore density with an aperture ratio of the lattice structured object.

According to still another embodiment of the present invention, thissystem further comprises a shape modification unit for modifying thethree dimensional data; wherein the shape modification unit comprises amodification site specification unit, by a computer, for displaying thethree-dimensional data on a computer display screen, and receiving aspecification of at least one polygon of a part of the three-dimensionaldata for which unevenness thereof is to be modified on the display; apolygon shifting unit, by a computer, for moving or distorting the atleast one polygon, with its center of gravity as a starting point,outward or inward of the blood vessel along a direction normal to thevascular wall surface, and a smoothing unit, by a computer, fordetecting an acute angle part in the at least one polygon that is movedor distorted by the polygon shifting unit, and smoothing out the acuteangle part.

In this case, it is preferable that the system further comprises a bloodflow characteristic determination unit for determining, from the statequantities of the blood flow obtained by the computation at each meshposition, a wall shear stress vector at each position of the wallsurface of the target vascular site, determining relative relationshipbetween a direction of the wall shear stress vector at a specific wallsurface position and directions of wall shear stress vectors at wallsurface positions surrounding the specific wall surface position, andfrom a morphology thereof, determining characteristics of the blood flowat the specific wall surface position, and outputting the same as adetermined result; and a display unit, by a computer, for displaying thedetermined result of the blood flow characteristic which is graphicallysuperposed onto a three-dimensional shape model.

Furthermore, it is preferable that the blood flow characteristicsdetermination unit determines whether the relative relationship betweenthe direction of the wall shear stress vector at the specific positionof the wall surface and the directions of the wall shear stress vectorsat positions on the wall surface surrounding the specific position is“parallel”, “confluent”, “rotational”, or “divergent”, and determinesthe blood flow characteristics to be benign (or non-malignant) if therelative relationship is “parallel”, otherwise malignant (ornon-benign).

In addition, it is desirable that if the blood flow characteristicsdetermination unit determines that the relative relationship between thedirection of the wall shear stress vector at the specific position ofthe wall surface and the directions of the wall shear stress vectors atpositions of the wall surface surrounding the specific position is“divergent”, the determination unit determines that thinning of thevascular wall at the specific position may occur, and the display unitoutputs the position of potential wall-thinning, superposed onto thethree-dimensional shape model graphically.

Furthermore, the blood flow characteristic determination unit preferablycomputes a rotation: rot τ, and a divergence: div τ, which are scalarquantities of a wall shear stress vector field: τ, from a relativeangular relationship between the wall shear stress vector τ at thespecific position of the wall surface and a plurality of wall shearstress vectors at positions of the wall surface surrounding the specificposition, defines these values as a flow disturbance index, and comparesthem with threshold values to determines the flow disturbance index tobe “parallel”, “confluent”, “rotational”, or “divergent”;

wherein if the value of rot τ of the flow disturbance index is either anegative or positive value outside a predetermined threshold range, itis determined as “rotational”;

if the value of div τ of the flow disturbance index is a negative valueoutside a predetermined threshold range, it is determined as“confluent”;

if the value of div τ of the flow disturbance index is a positive valueoutside a predetermined threshold range, it is determined as“divergent”; and

if the values of rot τ and div τ of the flow disturbance index are bothin a predetermined threshold range, it is determined as “parallel”. Inthis case, it is desirable that the blood flow characteristicsdetermination unit preferably regards the plurality of the wall shearstress vectors as unit vectors for mathematical operations, and thethreshold value to be compared with the rot τ and the div τ is zero.

In addition, the blood flow characteristics determination unitpreferably obtains the numerical values of the rot τ and div τ of theflow disturbance index by giving, as a weight coefficient, an indexvalue of a pressure that acts in a direction normal to the specific wallsurface position, to the rot τ and the div τ values.

Furthermore, it is desirable that the index value of the pressure thatis provided when calculating the values of the rot τ and the div τ ofthe flow disturbance index is a value obtained by dividing the pressureat the specific position of the wall surface by a mean value of pressureon the wall surface of the target vascular site.

In addition, the display unit preferably displays the numerical valuesof the rot τ and/or the div τ of the flow disturbance index with thethree-dimensional shape model on which they are superposed.

According to yet another embodiment of the present invention, the bloodflow characteristic determination unit computes a rotation rot τ and adivergence div τ of a wall shear stress vector field τ from a relativerelationship between a wall shear stress vector τ at a specific positionof the wall surface and a plurality of wall shear stress vectors atpositions of the wall surface surrounding the specific position,compares these values as a flow disturbance index with threshold values,and determines that the blood flow characteristics is benign (ornon-malignant) if the calculated values are within a threshold range;and the blood flow characteristics is malignant (or non-benign) if thecalculated values are outside the threshold range.

The second main aspect of the present invention provides a computersoftware program for operating the systems of the present invention.

The third main aspect of the present invention provides a method foroperating the systems of the present invention.

The characteristics of the present invention which are not describedabove are disclosed in the disclosure of embodiments of the presentinvention, and accompanied figures shown hereinafter in details so thatthose skilled in the art may work out the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a schematic diagram of an embodiment of the presentinvention.

FIG. 2 depicts the graphical user interface of the vascular shapeextraction unit.

FIG. 3 shows a flow chart of the vascular shape extraction unit.

FIG. 4 illustrates a vascular image that explains the extraction of avascular shape image.

FIG. 5 depicts the line-thinning step for vascular shapes.

FIG. 6 illustrates labeling the name of blood vessels including the mainblood vessels.

FIG. 7 shows processing of edging the extracted vascular shape.

FIG. 8 shows a schematic diagram of overall shape of blood vessels in abrain.

FIG. 9 depicts the graphical user interface of the surgical simulationunit.

FIG. 10 illustrates a schematic diagram of the surgical simulation unit.

FIG. 11 depicts a simulation in the first surgical simulation mode.

FIG. 12 depicts a simulation in the second surgical simulation mode.

FIG. 13 depicts a simulation in the third surgical simulation mode.

FIG. 14 illustrates an example of modification by applying the firstsurgical simulation mode.

FIG. 15 shows a schematic diagram of the fluid analysis unit.

FIG. 16 shows a flowchart of processes performed by the fluid analysisunit.

FIG. 17 depicts the graphical user interface of the fluid analysis unit.

FIG. 18 explains the level of detail of mesh.

FIG. 19 illustrates a diagram of the fluid shear stress.

FIG. 20 illustrates a diagram of the fluid shear stress.

FIG. 21 shows the global coordinate system for calculating the wallshear stress.

FIG. 22 shows the local coordinate system for calculating the wall shearstress.

FIG. 23 shows a graphical representation of superposition of shearstress vectors on the three-dimensional shape of blood vessels.

FIG. 24 shows a graphical representation of the shear stress vectors andthe pressure which are superposed on the three-dimensional shape ofblood vessels.

FIG. 25 explains the calculation of the flow disturbance index.

FIG. 26 shows a diagram for interpreting the flow disturbance index.

FIG. 27 shows the method for determining malignancy and benignancy withthe map of flow disturbance index.

FIG. 28 illustrates the method for determining wall thinning with theflow disturbance index.

FIG. 29 depicts the graphical user interface of the blood flowcharacteristics determination unit.

FIGS. 30A to 30D show the displayed result of the effectiveness of theflow disturbance index on determining the aneurysm wall thinningprocess.

FIG. 31 shows a schematic diagram of a surgical skill evaluation systemof another embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Referring to figures herein, an embodiment of the present invention isnow described in detail below. In the description hereinafter, acerebral aneurysm is presented as a cardiovascular disease that maybecome a subject of diagnosis and treatment.

(System for Diagnosing Blood Flow Characteristics Based onMalignant/Benign Blood Flow Patterns)

As described above, the first main aspect of the present invention is toprovide a diagnostic system for characterizing cerebral aneurysms. Thepresent invention associates the morphology of shear stress vectorsacting on the aneurysmal wall by blood flow, with the information on theluminal geometry, pathology, and wall thickness of aneurysm in order tocategorize the vectors to either a “malignant blood flow pattern” whichwould become a potential risk of appearance of lesion or its growth or a“benign blood flow pattern” which would not become the potential risk.The morphology of the shear stress vectors produced by the simulationdetermines whether the vectors imply either a malignant blood flowpattern or a benign blood flow pattern. If it is a malignant blood flowpattern, it would be a potential risk of appearance or growth of alesion, which may require considering a surgery whereas if it is abenign blood flow pattern, it would not be the potential risk, and mayavoid a risk of unnecessary surgery.

(System for Predicting Treatment Effect of Blood Vessel)

The second aspect of the present invention is to provide a system, e.g.,a system for predicting the treatment effect of a cerebral aneurysm,which is determined to have a malignant blood flow pattern.

In other words, a method for determining the blood flow characteristicsto be malignant or benign may be applied not only for pre-treatedaneurysms, but also post-treated aneurysms in terms of predicting thetreatment effect.

The surgical treatment for a cerebral aneurysm includes: 1) clipping, 2)coil embolization, and 3) stent placement (flow-diverting stent).

The clipping method blocks the blood flow inside a cerebral aneurysm byclosing a neck part of the aneurysm with a clip; i.e., it constructs anew vascular morphology that does not have the cerebral aneurysm. Thecoil embolization places a plural number of coils in an aneurysm tocreate thrombus in the lump for blocking the blood flow. Theflow-diverting stent method places a mesh like object that is made ofmetal or other materials at the neck of an aneurysm to reduce the fluidflow through the lump and form a thrombus in it for blocking the flow.

Those treatment methods have a common feature of blocking the fluid flowin a cerebral aneurysm, and they reconstruct a new lump neck, i.e., anew vascular shape by altering the cerebral aneurysm artificially. Apost-treatment complication may appear as the reconstructed vascularmorphology gradually changes in the course of time. For example, in acase of the coil embolization treatment, the reconstructed lump neck maybe compressed into the lumen by the fluid force, resulting in thereopening of a path between the main blood vessel and the lumen of lump,and thus a re-treatment is often required.

In such a case, first, the vascular morphology which is athree-dimensional model created by a computer is modified to create anew lump neck by a computer artificially so that a computer mayconstruct a vascular morphology similar to one to be formed byconducting an actual surgery. Second, the morphology of the shear stressvectors acting on the wall of the newly created blood vessel isvisualized by a simulation to apply the method for determining if thesimulated blood flow pattern is malignant or benign so that thetreatment effect by the surgery may be evaluated in advance. In otherwords, by applying the method for determining the malignant or thebenign blood flow pattern, it is possible to predict a direction ofprogress of whether the vascular cells such as endothelial cells growand adhere to the part of the blood vessel to reproduce the vasculartissue properly and regain the adequate mechanical strength, and thoseobservations by simulation may contribute to the accurate prediction ofthe treatment effect to reduce a post-surgical complication and evendeath of a patient.

(Configuration of a System for Determining the Blood FlowCharacteristics Diagnosis/Predicting the Treatment Effect Related tothis Embodiment)

FIG. 1 shows a schematic diagram of a system for determining the bloodflow characteristics/predicting the treatment effect related to thisembodiment. The blood flow characteristics determination/treatmenteffect prediction system corresponds to the first and the second aspectsof the present invention, which has the following two capabilities.

(1) For considering if the subjective cerebral aneurysm has aprobability of an appearance of lesion or its potential growth, thesystem determines automatically whether the target vascular site of asubject is either a benign blood flow pattern that would not rupture thecerebral aneurysm or a malignant (non-benign) blood flow that wouldrupture the cerebral aneurysm.

(2) When the cerebral aneurysm is to be surgically treated, byconducting a surgical simulation in order to predict the post-surgicalblood flow, the system determines automatically whether the blood flowpattern would be either a benign blood flow that would not develop arisk of post-surgical complication or death, or a malignant blood flowthat would develop a risk of post-surgical complication or death.

In order to perform those functions, this system for diagnosing bloodflow characteristics/predicting the treatment effect is installed at asite (e.g., a hospital) of a user such as a doctor as shown in FIG. 1,which equips with an image capture device 1 that takes images ofcerebral aneurysm and surrounding target vascular sites, a user terminal2 with which a user such as a doctor may operate the system, and a bloodflow characteristics diagnostic/treatment effect prediction systemserver 3 which connects the image capture device 1 and the user terminal2 through a communication network (an in-hospital LAN, anout-of-hospital WAN, or a designated communication line).

Here, the image capture device 1 may be an instrument that acquires atomographic image of the target vascular site, by using a ComputedTomography (CT) scanner, an Magnetic Resonance Imaging (MRI) system, aDigital Subtraction Angiography (DSA) equipment, and other medicalinstruments that acquire images of the target vascular site by applyingmethods such as the ultrasound Doppler and the near infrared imagingtechnology.

The aforementioned user terminal 2 may be a workstation consisting of astandard personal computer that runs a display software program such asa browser capable of displaying a graphical interface for establishingcommunication with a server of the blood flow characteristicsdetermination/treatment effect prediction system.

The server 3 of the blood flow characteristics determination/treatmenteffect prediction system consist of a program storage unit 8 connectedwith a bus line 7 that connects an input/output interface 4 used forestablishing communication with the communication network, a memory 5,and a CPU 6. The program storage unit 8 is configured with a vascularshape extraction unit (i-Vessel) 10 that produces a set ofthree-dimensional data of a target vascular site by using the image dataacquired by the image capture device 1, a surgical simulation unit(i-Surgery) 11 that runs a surgical simulation by manipulating thethree-dimensional data, a fluid analysis unit (i-CFD) 12 that computesthe state quantities of the blood flow at the target vascular site, ablood flow characteristics determination unit (i-Flow) 13 thatdetermines the blood flow at the target vascular site whether it isbenign or malignant, and a display unit 14 that has a user graphicalinterface produced by the system and a display screen to show the image,the analysis result and the determined outcome. There are two databasesconnected with the bus line 7: a simulation setting DB 15 that storesvarious setting information for conducting the simulation, and asimulation result DB 16 that stores outcomes of the simulation and theanalysis.

The components of the server 3 (the vascular shape extraction unit 10,the surgical simulation unit 11, the fluid analysis unit 12, and theblood flow determination unit 13) are actually constructed by computersoftware programs that are stored in a memory area of a hard drive of acomputer, and the CPU 6 deploys the software programs from the harddrive to the memory 5 for executing the programs so that the componentsof the present invention performs their functions. A single computer mayconfigure the server 3, or multiple computers may configure adistributed server as the server 3 as well.

In the above example, the server 3 of the blood flow characteristicsdetermination/treatment effect prediction system connects with a userterminal 2 in a hospital through a communication network, and the servermay be installed in a hospital or in a high speed process center 9outside a hospital. In the latter case, the server is preferablyconfigured to receive data and instructions from a number of userterminals 2 and image capture devices 1 of several hospital sites, andexecutes highly accurate fluid analysis using a high speed processor,and then feeds back the analysis outcome to the user terminals in eachhospital so that a user such as a doctor may display the analysisoutcome on screen for a patient and other people on the spot.

Referring to actual system operations, the capability of this blood flowcharacteristics determination/treatment effect prediction system isdisclosed hereinafter.

(User Graphical Interface)

FIG. 2 depicts the user graphical interface (GUI) 17 that is created byemploying the display unit 14 of the server 3, and displayed on the userterminal 2. This interface configures an integrated interface functionthat operates the vascular shape extraction unit (i-Vessel) 10, thesurgical simulation unit (i-Surgery) 11, the fluid analysis unit (i-CFD)12, and the blood flow characteristics determination unit (i-Flow)together.

For example, FIG. 2 shows an example when the vascular shape extractionunit “i-Vessel” 10, whose function is described below, is selected fromthe menu located at the top of the display screen. In a similar fashion,the interface (to be described hereinafter) may switch the function byselecting i-Surgery 11, i-CFD 12, or i-Flow 13.

There was no such integrated system in the prior art where simplyassembled individual systems through separate interfaces were used. Aconventional system is anticipated to have technological difficulties inpractical clinical applications and standardization of the analysisconditions because: (1) a user has to employee a plural number ofsystems one after another in order to analyze a single case whilespending at least several hours in a workplace, and (2) each system isdesigned to have large flexibility and versatility for engineering workflows by adjusting many and different parameters for setting up ananalysis routine, requiring user's knowledge and skill to optimize theparameters, which may not be suitable for medical applications.

This embodiment of the blood flow characteristicsdetermination/treatment effect prediction system needs to be used aspart of medical treatment in an extremely busy clinical environment.Therefore, the time restriction imposed on a medical practitioner andthe inconsistency of analytical conditions among different users andfacilities are major technical issues to be solved. It also needs toconsider the factor to be included that a user, who is a clinical doctoror a radiology technician, is not an engineer and unaware of theknowledge of fluid dynamics. The embodiment of this system integratesthe system units and a single interface 17 may execute an automaticcontrol process, which eliminates the technological issues describedabove.

The embodiment of the system holds the optimal values of a group of theoperational conditions for each application as a “module”, which allowsa user to carry out an automatic control process for a blood flowanalysis required for a particular user's application without settingthe group of the operational conditions.

(Vascular Shape Extraction Unit) FIG. 3 shows a flow chart of theprocess steps of the vascular shape extraction unit, and FIGS. 4 to 9illustrate vascular images that explain the process steps.

Step S1-1 inputs a set of image data, which an image capture deviceacquired from the target vascular site, in the DICOM format. Step S1-2recognizes the orientation of the image (i.e., up, down, right, and leftof the image) automatically or specifies the orientation manually. Asdescribed above, FIG. 2 depicts the user interface of the vascular shapeextraction unit (i-Vessel). The interface that recognizes the imageorientation is the display part 41 which is one of four display parts 41to 44 and located in the upper left corner of FIG. 2. As the displayparts 42 and 43 show, when a three-dimensional vascular shape isvisualized by applying a volume rendering method known to those skilledin the art, the orientation of the blood vessel to be displayed may bespecified by pushing “Anterior (A)”, “Posterior (P)”, “Left (L)”, or“Right (R)” of a button 18 so that the vascular image orientation isaligned with the direction of “Anterior (A)”, “Posterior (P)”, “Left(L)”, or “Right (R)”.

Next, on the same screen (FIG. 2), an anatomical part is specified byselecting, e.g., a radio button 24 (Step S1-3). The anatomical partspecified in this step is used for labeling blood vessels automaticallyin a step described hereinafter. For example, if a cerebral aneurysm isfound in the right middle cerebral artery (MCA), “Right AnteriorCirculation” is selected. Similarly, “Left Anterior Circulation”,“Anterior Circulation”, or “Posterior Circulation” may be also selected.The item 19 shown in FIG. 3 indicates that the anatomical part is storedin the simulation setting DB 15.

Step S1-4 and following steps construct the three-dimensional vascularmorphology (the three-dimensional shape data) by applying the thresholdmethod or the gradient method combined with the region growing method(and other methods shown in FIG. 2, including: the “Selection (where auser specifies a region of interest on screen to determine a regioncontaining a targeted blood vessel from a three-dimensional structurethat is extracted by applying the threshold method (or the gradientmethod))”, “Connectivity (where the user specifies the targeted bloodvessel to extract the targeted blood vessel by selectively takingcontinuous voxels only)”, “Extension (which is an region growing methodincluding the threshold method (or the gradient method) and thecontinuity of voxels, and adds blood vessels that need to be used butdeleted in the blood vessel extraction Step)”, and “Removal (where theuser deletes the blood vessels that is not required).” For this purpose,Step S1-4 extracts a targeted vascular region. The extraction isexecuted by using e.g., the threshold or the gradient method.

FIG. 4 shows an example of the extraction using the threshold method.

The threshold method uses, for instance, the absolute value or thenormalized relative value of luminance. In this embodiment, thethreshold setting unit 45 applies the slider method to select thehistogram threshold value and changes the threshold value whileobserving the image on the display unit 42 to extract thecharacteristics that are intrinsic to the vascular wall. On the otherhand, the gradient method calculates the luminance gradient of thebrightness from the luminance distribution. After the extraction step, auser pushes the “Fix” button 46 on the screen shown in FIG. 2 toactivate the vascular shape extraction unit 10 to remove noise from thevascular surface by using the optimal threshold value for a given imagetype (Step S1-5), and then construct three-dimensional shape data bydividing the region into polygons to complete extracting the targetedvascular region (Step S1-6). FIG. 4 depicts a schematic diagram ofextraction of vascular morphology in this step. These threshold valuesare stored in the simulation setting DB 15 (the item 29 shown in thefigures attached therein).

Then, a user presses the “Lesion” button 47 on the screen shown in FIG.2 by using a device such as the mouse to specify the lesion manually(Step S1-7). Step S1-8 executes the line thinning routine to create thecenter lines of blood vessels. A user may automatically perform the linethinning routine by pushing the “Label” button on the screen of FIG. 2.There are various well-known algorithms for the line thinning routine.FIG. 5 shows the actual line thinning step. After acquiring the centerlines, Step S1-9 divides the center lines into multiple segments each ofwhich corresponds to a blood vessel. As shown in FIG. 5, thesegment-division routine may be performed by segmenting the center linesat vascular bifurcation points A, B, C, D, etc. FIG. 6 enlarges thesegmented regions. In this figure, the segments (V1, V2, . . . ) betweentwo adjacent bifurcations, A, B, C, . . . , are called the blood vesselelements. Step 1-10 obtains several cross-sectional areas (as shown inFIG. 6) that are perpendicular to the center line of each blood vesselsegment, and then calculates the equivalent diameter of thecross-sections for measuring the shape 25 of each segment.

Step S1-11 labels the name of each blood vessel segment automatically.Among the several blood vessel segments V1, V2, V3, . . . , the one thathas the largest median of the various equivalent diameters calculatedfrom the cross-sections 25 is determined to be the main blood vessel andlabeled the name. (The mean value may not accurately represent the mainblood vessel if there is an extraordinary large diameter due to acerebral aneurysm in the blood vessel.) In this embodiment of thepresent invention, the labeling routine may be executed automatically asthe anatomical lesion is specified. In other words, if the left anteriorcirculation is selected, the main blood vessel, (which is the bloodvessel segment with the largest median of the equivalent diameters) islabeled the “left internal carotid artery” whereas, if a posteriorcirculation is selected, the main blood vessel is labeled the “basilarartery.” These main blood vessels are identified as the ones with thelargest equivalent diameters. Shape parameters other than the equivalentdiameter or their combinations may be applied for the labeling routine.As shown in FIG. 3, the simulation setup DB 9 stores the anatomicallesion information 19, the names of the main blood vessel 20, and thenames of branched blood vessels 21, as related to each other, which thelabeling unit 35 of the vascular shape extraction unit 10 uses as “alabeling template” for the automatic labeling routine.

Thus, Step S1-11 performs the aforementioned labeling routine for themain blood vessels V2, V3, . . . , followed by tracking the branchedblood vessels individually to label the names of blood vessels at eachbranch by identifying them according to the information stored in the DB9. In the embodiment of the present invention, labeling the branchedblood vessels is limited to carry out down to a 5 to 10 sub-layers fromthe main blood vessels. As described herein, once the name of the mainblood vessel 20 is determined according to the information DB 19 of eachanatomical lesion, the labeling routine of the branched blood vesselsmay be automatically performed by following the relation between themain blood vessel name 20 and the branched blood vessel names 21, whichis stored in the database 9.

Next, Steps, S1-12 and S1-13, after labeling, construct thecross-section of a blood vessel by making the inlet and the outlet ofthe blood vessel perpendicular to the central line based on theorientation (the vertical and the horizontal directions) of an image andthe anatomical lesion specified as the targeted blood vessel that isselected in Step S1-2. FIG. 7 illustrates the cross-sectionalconstruction. Step S1-4 automatically outputs polygon data as thethree-dimensional shape. At the same time, the shape data 22 of eachblood vessel (which is called the labeling information 23), which arelabeled automatically, are calculated and recorded into the simulationresult DB 16 automatically (FIG. 3). A user may confirm if the processis appropriate by checking the interface 17 displayed on screen. Theremay be a case where labeling is not processed properly in the automaticprocess. For example, there is a case where a patient with a congenitalvascular malformation would not have a blood vessel at a correspondinglocation. In such a case, the diagnostic simulation system may beconfigured so that clicking on the falsely labeled blood vessel changesthe name of the selected blood vessel. The names 20 and 21 of thesetting DB21 may be also changed at this time. After the manual process,clicking the <End> button outputs the result automatically andoverwrites to update DB15 and DB16. The name of a file output isconfigured according to the patient ID that may be extracted from theDICOM header information with which the file format may be obtained,which allows a user to eliminate inputting the file format manually. Thesurgery simulation unit 11, the fluid analysis unit 12, and the bloodflow characteristics determination unit 13 have the same file nameprotocol as described hereinafter.

FIG. 8 overviews a list of the names of cerebral blood vessels. FIG. 8is for the anterior and the posterior circulations. For example, theanterior communicating artery, a lesion where cerebral aneurysm oftenappears, runs across the left and the right anterior circulations, andhence it is necessary to target the overall anterior circulation foranalysis.

(Surgery Simulation Unit)

FIG. 9 depicts a schematic diagram of the user graphical interface 17 ofthe surgery simulation unit 11; FIG. 10 shows the operational flow chartof the surgery simulation unit 11; and FIGS. 11, 12, and 13 illustratethe surgical modes. FIG. 14 is a schematic diagram of the shapemodification unit 34 that modifies the three-dimensional morphologicalunit for the surgical simulation.

In this example, the interface 17 shown in FIG. 9 allows a user toselect a surgical mode from the three predetermined modes,“Clipping/Coiling” 50 as the first surgical mode, “Stenting” 51 as thesecond surgical mode, or “Flow-diverting” as the third surgical mode.With this surgical mode selection, the surgical simulation unit 11 mayproduce the optimal vascular shape to reproduce the post-surgical bloodflow.

In the aforementioned three modes, the first surgical simulation modecuts out a lesion and reconstructs the vascular wall surface(Clipping/Coiling); the second surgical simulation mode reconstructs thevascular surface by smoothing the uneven surface of the lesion(Stenting); and the third surgical simulation mode places a lattice likeobject on an arbitrary vascular cross-section (Flow-diverting stent).

The vascular shape modification method (the item 37 in FIG. 15)corresponding to the first surgical simulation mode is a program group50 (consisting of <Positioning>, <Removal>, <Recon>, <Shaping>, and<Label>) that simulates surgical clipping or coil embolization thatcompletely closes an aneurysm lumen, in order to conduct a pre-surgicalestimation of the fluid force which exerts on the neck of aneurysmformed by the surgery. The vascular shape modification methodcorresponding to the second simulation mode is a collection of programs51 (consisting of <Positioning>, <Fitting>, <Shaping>, and <Label>)which simulates a stent placement that enlarges a vascular stenosis dueto arteriosclerosis by employing a medical device such as a stent toconduct a pre-surgical estimation of the fluid force which exerts on thelesion formed by the surgery. The vascular shape modification methodcorresponding to the third surgical simulation is a collection ofprograms 52 (consisting of <Positioning>, <Porosity>, <Shaping>, and<Label>) which simulates a treatment of cerebral aneurysm by using theflow-diverting stent to estimate the effect of reducing the flow throughthe aneurysm.

This simulation is conducted by actually modifying the three-dimensionalvascular shape data, and the surgical simulation unit has the treatmentreceiving unit 73 and the shape modification unit 34 as shown in FIG.15. Below is a description of the unit configuration along with theirprocessing operations. The selectable surgical modes (which are thefirst to the third surgical simulation mode in this example) and theconcrete methods for modifying the vascular morphology defined inrelation to the surgical modes are stored in the simulation setting DB15 as shown the items 36 and 37 in FIG. 15.

First, on the screen of the user graphics interface 17, a user pushesthe <Surgery> button 11 to display the vascular morphology that iscreated by the vascular shape extraction unit through the browserdisplay of the user terminal 2. (Step 2-0: the display part 54 on theupper left corner of FIG. 9.) When a user activates the first surgerysimulation mode (the item 50 in FIG. 9) on the interface 17, thetreatment receiving unit 73 loads the vascular shape modification method37 (which is the program group 50 consisting of <Positioning>,<Removal>, <Recon>, <Shaping>, and <Label>) from the setting DB 15, andthe user selects a lesion by using the <Positioning> (Step 2-1). If theuser selects <Positioning>, the modified lesion specification unit 38displays the specified region on the user interface 17. (The displaypart of the upper right corner of FIG. 9.) Because the three-dimensionalshape data are polygon data that are a collection of minute trianglesthat configure the surfaces and the ends blood vessel surface and theends of blood vessels, the specified region may be enlarged or shrunkfor the purpose of the surgical simulation. If the user selects<Removal>, it cuts out the triangle element selected by the polygonmoving unit 39 shown in FIG. 15 (Step S2-2). Pushing the <Recon> buttonreconstructs a surface on the dissected part by using polygons. Pushingthe <Shaping> button activates the modification specification unit 38and a user may activate the modification specification unit 39 andoperate the mouse to carry out smoothing the reconstructed surface (Step2-3), and then <Label> defines labeling the new surface (the Labelingunit 35) (Step S2-4). The surface reconstruction may be executed bycalculating the center of mass of the dissected region and connecting itwith the vertexes of the triangle elements at the edge of the dissectedregion. For smoothing the surface, a user freely move the center of massof the triangle to the normal direction of the outer (or inner)peripheral direction of the dissected surface by pushing the mouse wheelbutton, i.e., shifts the center of mass which is the unique point of thetriangle to a different location to distort the triangle artificially. Ashape with an acute angle by moving the center of mass may be smoothedout simultaneously (by using the aforementioned units 38 and 39).

With the user interface shown in FIG. 9, a user uses the display parts55 and 56, <<Post-surgery>>, at the left and right bottom to display animage of lesion after surgery and conduct surgical simulations using theprogram group. After completing the labeling step, <End> finalizes theshape, and similar to the vascular shape extraction unit, polygon dataare stored automatically, updating the simulation result DB 16 (Step2-13: Updates of labeling information 23 and three-dimensional shapedata 22). For comparing a plural number of surgical simulations byrepeating the previous steps, there are the display parts of<<Post-surgery>> at the right bottom 55 and at the left bottom 56<<Post-surgery #1 and #2>>. (The comparison display part of the presentinvention).

FIG. 11 depicts a diagram of an example of vascular shape modificationin the first surgical simulation, and FIGS. 14A and B show thethree-dimensional shape before and after the simulation (correspondingto before and after a treatment by clipping). As shown herein, deletingpolygons that configure a shape of the cerebral aneurysm may reproducethree-dimensional vascular shape which exhibits the blood flowcharacteristics after conducting the clipping treatment. Therefore, auser may arbitrarily adjust the cross-sectional shape of a cerebralaneurysm that is constructed by a clipping treatment or a coilembolization in order to simulate and analyze the post-surgical bloodflow.

In the second surgical simulation mode 51, similar to the aforementionedsimulation, using <Positioning>, the lesion is selected and scaled-upand down (Step S2-5, the display part 55). In the next step, with<Fitting>, the center of gravity of the lesion is calculated, and usingthe center as the starting point, a polygon is moved in the normaldirection to the vascular wall, and a polynomial fitting interpolatesthe lesion morphology (Step S2-6). Then, with <Shaping>, smoothing outof the lesion is executed using the mouse (Step S2-7), and finally, amethod similar to the aforementioned first surgical simulation performsthe labeling routine (Step S2-8). FIG. 12 illustrates a diagram of anexample of the shape modification with the second surgical simulation.

In the third surgical simulation mode 52, a user uses <Positioning> toconstruct a new surface inside the three-dimensional vascular morphology(Step S2-9). Next, for a specified surface, <Porosity> defines alattice-like object (Step S2-10), smoothing out the surface by applyinga method similar to the aforementioned method (Step S2-11), and executeslabeling (Step S2-12). The lattice-structured object used for thevascular shape modification method 37 (FIG. 15) attempts to simulate theflow-diverting stent. The lattice-structured object is a homogeneousporous media that a user may adjust the aperture ratio by using a pulldown menu. The user may also create an inhomogeneous media by adjustingthe aperture ratio and the shape of a pours media. FIG. 13 shows adiagram of an example of shape modification by the third surgicalsimulation mode. In this figure, the lattice-like object is the item 25.The blood flow simulation using the porous media may also simulate theblood flow after conducting a coil embolization surgery. Theaforementioned coil embolization assumes a complete embolization in thelump. This actually corresponds to a condition of adequate embolizationin the lump when the time subsequently elapsed after surgery. On theother hand, there is blood flow in the coil until it is completelyblocked. Whether the blood flow may be simulated or not is crucial todetermine the coil filling ratio (which is the volume ratio of the coilto the lump). The above-described flow-diverting stent uses the porousmedia as a two-dimensional structure, which may extend to thethree-dimensional structure to simulate the condition immediately aftera coil embolization. In other words, it is possible to add a function ofsimulating the coil filling ratio by using the aforementioned <Porosity>to place a porous media in the lump and simulate the coil filling ratiowith the aperture ratio.

(Flow Analysis Unit)

In the next step, the fluid analysis unit 12 obtains the blood fluidvelocity and pressure (which is the state variable 33) at each unit areaof the target vascular site using the three-dimensional shape data ofthe target vascular site created by the vascular shape extraction unit10 (and the surgical simulation unit 11).

FIG. 16 is the flow chart of processes that the fluid analysis unit 12executes, and FIG. 17 shows an example of selecting “CFD” 12 from themenu of the user graphic interface 17.

In Step S3-1, the fluid analysis unit 12 selects and reads the vascularshape data for calculation from the three-dimensional shape data of thetarget vascular site which the vascular shape extraction unit 10 (andthe surgical simulation unit 11). The selected data is displayed on thedisplay parts 58, 59, and 60 which locate the upper left corner of theinterface 17 as shown in FIG. 17. In this example, the display unit 58displays the shape data of Pre-Surgery, the display part 59 displays theshape data of Post-Surgery #2, and the display part 60 displays theshape data of Post-Surgery #1.

In the next step, Step S3-2, a user selects a “module.” As shown in FIG.17, for selecting a “module”, there are three buttons displayed on theuser graphic interface 17 and available for selection: “On-site” 26,“Quick” 27, and “Precision” 28.

The system configures a default set of mathematical operation values 40(FIGS. 1 and 16) to execute computations with appropriate condition andprecision after a user selects a module from the three modules.Considering the time restriction in the clinical practice and the user'snon-expertise of the fluid analysis, this configuration of integratingthe analysis conditions is realized to fulfill the demand from theworkplace, and to achieve reproducibility and standardization of theanalysis conditions. The mathematical operational condition for“On-site” adopts a steady flow analysis. The blood flow is an unsteadyflow which is called the pulsatile flow produced by the cardiacpulsation. Calculation of an unsteady flow executes an iterativecalculation that converges the solution at each time interval for thetime-varying flow, which requires a large calculation load on themathematical operation unit. On the other hand, the steady flow is notnecessarily quite different from the pulsatile flow. In particular, thecerebral blood vessel is a region where the Reynolds number of the bloodflow is relatively small, whence the blood flow is laminar in thepulsatile period, and does not have the transient vortex observed inturbulence with a large Reynolds number. In other words, the blood flowin the pulsatile period has a strong similarity in the variation of flowrate. Therefore, if a blood flow corresponding to the time-averaged flowmay be reproduced, it is possible to understand the flow patter as thepulsatile flow. The On-site module is an analysis method that issupported by the experimental and analytical data of this approach.

On the other hand, “Quick” and “Precision” have the set of mathematicaloperation condition values 40 for the pulsatile flow. Unlike “Quick”,“Precision” sets a condition with a capability of dealing with a changefrom the laminar to the turbulent pulsatile flow. The set DB 15pre-stores various conditions, including the level of detail of mesh,the physical property of blood, the wall boundary condition, the inletboundary condition, the outlet boundary condition and the discretizingcondition, as the set of mathematical operation condition values 40. Itwould often take several days for a single fast processor to completeanalyzing “Precision.” In the embodiment of the present invention, thefirst processor 41 of the fluid analysis unit 12 executes the relativelylight process of the On-site while the second processor 42 of a fastprocessing center 9 in a remote area carries out the heavy process ofthe Precision. In other words, the precision module is configured inorder to perform the following job flow: the data for processing thePrecision task is automatically transferred to the process centeroutside a hospital through a telecommunication network,parallel-processed with a plural number of fast processors, and thenreturned the analysis outcome to the hospital through the network.

In Step S3-3 and following steps, a user pushes the Run button 62 of theinterface 17 shown in FIG. 17 to select the set of the mathematicaloperation values 40 for a selected module, and automatically performsthe calculation. Step S3-3 divides the target vascular site into aplural number of triangles of the finite element method based on thethree-dimensional shape data. The embodiment of the present inventioncreates a mesh structure using the level of detail of mesh for the bloodvessel size based on the vascular labeling conducted by the vascularshape extraction unit 10. In other words, in this embodiment, the set ofthe mathematical operational condition values 40 stores the level ofdetail of mesh for the mesh dividing in relation to the blood vesselname, or dynamically determines the level of detail of mesh according tothe vascular cross-section. Thus, this system may read the level ofdetail of mesh out of the set DB 15 according to the labeling and use itfor the mathematical operation. That is, each level of detail of meshmay be determined according to the module selected and the vasculartype.

FIGS. 18A and 18B illustrate an example of varying the level of detailof mesh per blood vessel. In this example, the resolution for theophthalmic artery of diameter 1 mm is set to be higher than the arteryinside diameter 5 mm.

D_(mesh) of this embodiment of the present invention is defined asfollows.D _(mesh) =D _(base) ×K _(scale) ×K _(module)where D_(mesh) is the level of detail of mesh (which is therepresentative diameter D_(mesh) in this embodiment), D_(base) is thesize of the base mesh (which is a constant independent of the scalefactor), K_(scale) is a scale factor which varies according to thevascular size, and K_(module) is a scale factor which varies accordingto the module selected.

An ordinary finite element analysis does not consider the scale factordefined above but determined the mesh size by the base mesh alone. Forthis reason, the prior art was unable to include the variation of eachvascular diameter. However, the embodiment of the present invention mayovercome the technological issue of the prior art.

An example is described hereinafter. In the example, the fluid analysisunit 12 calculates the equivalent vascular diameter D by using the bloodvessel volume, the length of the central line of the blood vessel, andthe approximate cylinder of the blood vessel for quantitating thevascular size.

1) For using the On-site, Quick module,

D_(base)=0.1 mm

K_(scale)=0.2 (if D<1.5 mm)

K_(scale)=1.0 (if D≧1.5 mm)

K_(module)=1

(In other words, in this module, the mesh size of the arteriole havingthe equivalent diameter D less than ⅕ mm is only refined to ⅕ of thebase mesh.)

2) For using the Precision module,

D_(base)=0.1 mm

K_(scale)=0.2 (if D<1.5 mm)

K_(scale)=1.0 (if D≧1.5 mm)

K_(module)=0.5

(In this example, K_(module)=0.5 and the mesh is refined overall.)

With the above method, the mesh size would change abruptly at a vascularbranch. The discontinuous change of the mesh increases the morphologicaldistortion, which may lead to degrade the convergence of computation.For overcoming this computational issue, the embodiment of the presentinvention creates the mesh by using the aforementioned method, thenproviding the upper limit for the mesh distortion and repeatedly carriesout the smoothing process so that the maximum distortion settles withinthe threshold value.

The analysis method of the prior art was unable to change the mesh sizedynamically for the vascular size, and hence it used the same level ofdetail of mesh for both large and small blood vessels. Although a meshsize which is adequate enough to analyzing a large blood vesselconversely shows poor analytical precision for a small blood vesselwhereas a mesh size adequate enough to analyzing a small blood vesselcreates the level of detail of mesh unnecessarily to prolong the timefor analysis, the present invention solves the technological problem.

The following steps S3-4 to S3-8 read out the set of mathematicaloperation conditions 40, which stores the physical property of blood,the boundary condition, and the analysis condition, from theaforementioned set DB 15, and Step S3-8 executes the mathematicaloperation based on these conditions. Specifically, the fluid analysisunit 12 solves a second order nonlinear partial differential equationthat describes the motion of fluid, called the Navier-Stokes equation,by applying the finite element method, and obtains the fluid velocityand pressure at each mesh. In this case, the solution of the finiteelement method (the fluid velocity U and the pressure P) is obtained inthe three directions, the X-global, the Y-global, and the Z-global, ofthe global coordinate frame.

In the mathematical operation conditions 40, the physical property ofblood includes the viscosity and density. The boundary condition is thefluid conditions at the inlet and outlet of the targeted lesion foranalysis and the fluid condition applies the statistical mean values offluid velocity and pressure.

Although the set condition selects a default condition automaticallyaccording to the selected module as described above, this embodiment ofthe present invention preferably has an additional capability ofmanually inputting a condition into the fluid analysis unit 12 prior toexecution of the mathematical operation.

After the calculation starts automatically, Step S3-10 displays theresidual and the calculation repeats until the result satisfies thepredetermined converging criterion. If the residual does not satisfy thepredetermined converging criterion even after repeating the maximumnumber of iterations permitted, the calculation is determined to benon-converging (Step S3-11). In this case, optimization of the meshdistortion will be carried out (Step S3-12), and the calculation will beresumed. Once the residual reaches within the predetermined convergingrange, the completion of calculation is displayed (Step S3-13). Thecalculation result (which is the state quantities (U and P)) isautomatically stored in the DB 16 in a similar manner described above.

The mathematical operation adopted herein is not only for the finiteelement method but also for numerical analyses of the differentialequation of fluid flow, such as the finite volume method and the finitedifference method.

(Blood Flow Characteristics Determination Device)

There is a software program that enables a computer to perform thefollowing functions and installed in the blood flow characteristicsdetermination unit 13. That is, as shown in FIG. 1, the blood flowcharacteristics determination unit 13 has the wall shear stress vectorcalculation unit 30 that obtains the fluid shear stress and its vector(the “wall shear stress vector”, hereinafter) exerted on the vascularwall by the blood flow by using the fluid velocity and pressure for eachmesh calculated by the fluid analysis unit, the flow disturbance indexcalculation unit 31 that obtains the numerical index (i.e., the flowdisturbance index) from the wall shear stress vector, and thedetermination unit 32 that determines the blood flow characteristics ateach mesh according to the flow disturbance index.

FIGS. 19 and 20 depict schematic diagrams to obtain the shear stressvector τ (x, y, z) based on the fluid velocity U and the pressure Pobtained at each mesh in the wall shear stress vector calculation unit30.

As shown in FIG. 19, the wall shear stress is the fluid viscous forceexerting on an area element of the vascular lumen in the paralleldirection, and the wall shear stress vector is the vector expression ofthe stress including the direction of the force. The acting direction ofthe wall shear stress vector is perpendicular to the pressure which isthe fluid force exerting on the center of the mass of the area elementin the normal direction of the area.

For describing the figure, it is necessary to understand thetransformation from the global coordinate system to the local coordinatesystem. In other words, the pressure P and the velocity U for obtainingthe shear stress vector are calculated in the global coordinate systemwhereas the shear stress force at a location on the vascular wall is inthe tangential direction of the wall surface, and calculation of itsmagnitude requires transforming the pressure and the velocity from theglobal coordinate system to the local coordinate system of the vascularwall.

Here, as shown in FIG. 21, the global coordinate system of this systemof this invention is a unique reference coordinate to show a universalposition of mesh nodes forming the vascular surface and lumen. Thefinite element method and the finite volume method represent the subjectfor calculation as a set of geometrical elements (such as triangleelements, tetrahedral elements, and hexagonal elements). Each elementhas a vertex called the node, and the position information is retainedusing the global coordinate system such as (X1_(g), Y1_(g), Z1_(g)),(X2_(g), Y2_(g), Z2_(g)), and (X3_(g), Y3_(g), Z3_(g)).

As shown in FIG. 22, the local coordinate system is a frame of referencethat is locally defined for each triangular element (or polygon)configuring the vascular surface, and usually, the center of gravity ofthe triangle is the origin and one axis (i.e., the Z axis) is taken tobe the normal vector to the area. The local coordinates of each point ofcontact of the area element are (X1₁, Y1₁, Z1₁), (X2₁, Y2₁, Z2₁), and(X3₁, Y3₁, Z3₁). The position in the global coordinate system and thatof the local coordinate system may be mutually transformed by using theposition of the center of mass of the triangular element and thedirection of the area normal vector.

A method for obtaining the wall shear stress is explained below.

The first step is calculation of the velocity and the pressure at eachnode in the global coordinate system by using the output from the fluidanalysis unit 12 (i-CFD). The next Step is specification of a trianglewhere the wall shear stress vectors to be calculated. The localcoordinate system is configured for the specified triangular element. Inthe local coordinate system, a position G where the shear stress vectoris calculated is determined. (For each triangular element, the distancefrom the wall is usually kept to be constant, e.g., 0.1 mm inward fromthe wall.) The fluid velocity at the position G is zero because itlocates on the wall surface as shown in FIG. 20.

Letting Ut be the fluid velocity at a position from the position G by adistance t, which is assumed to be very small compared with the boundarylayer thickness, in the normal direction (i.e., the Z direction of thelocal coordinate system), the fluid velocity Ut is approximatelyproportional to the distance n from the point G, and may be expressed asUn=n·dUt/dZ.

According to the action-reaction law, the resistive force against movingthe point at distance n at this fluid velocity has the same magnitude ofthe force that fixes the point, and both of them are proportional to thefluid velocity Ut and also inversely proportional to the distance Z.Therefore, the force τ per unit area at the point G in contact with thefluid becomesτ=μ·dUt/dZ.

That is, the wall shear stress vector is the product of the viscouscoefficient and the rate of changing the velocity vector parallel to thearea element in the normal direction. There are several methods forcalculating the changing rate of the velocity vector parallel to thearea element in the normal direction. For example, it is possible toobtain the velocity at each point of a plural number of points on the Z1axis by interpolating the surrounding velocity vectors. In this case,because the distance between the individual surrounding velocity vectorand the candidate point is different, the interpolation requires aweight function of the distance. Since the surrounding velocity vectoris expressed in the global coordinate system, the velocity vector afterinterpolation is expressed in the local coordinate system to calculatethe velocity component parallel to the surface at each candidate point.When the changing rate in the normal direction is to be calculatedlater, the first order approximation using a single candidate point nearthe wall may be applied, or a higher order of mathematicaldifferentiation where a polynomial approximation using a plural numberof candidate points near the wall may be calculated followed bymathematical differentiation may be executed.

For calculating the aforementioned changing rate from velocity U(Xg, Yg,Zg) in the global coordinate system, the following approach may beapplied: decomposing the velocity vector at the distance t in the localcoordinate system (X1, Y1, Z1), and solving τ=μ·dUt/dZ in the coordinate(X1, Y1) parallel to the wall surface in each local coordinate system(the Z component is zero).

In other words,τ(X1)=μ·dUt(X1)/dZ,andτ(Y1)=μ·dUt(Y1)/dZare calculated.

The vector values τ (X1, Y1) in all local coordinate systems form thewall shear stress vector. Therefore, on an area element in contact withthe wall surface, the wall shear stress vector has the x and the ycomponents defined by the x and the y directions of the area element.

FIG. 23 illustrates the shear stress vectors along the vascular wall byusing the method described above and attached to a three-dimensionalshape model.

It should be noted that there is force exerting on the vascular wall inthe tangential direction, and there is also the pressure P in thedirection of collision against the wall. The pressure at the point G inthe global coordinate system will be in the Z1 direction of the localcoordinate system after the coordinate transformation. FIG. 24superposes the colorized pressure values on FIG. 23. Area with lightercolor indicates higher pressure.

The wall shear stress 71 and its vector 72 obtained for each polygon inthis manner are stored in the simulation result DB 16.

(Flow Disturbance Index Calculation Unit)

Next, the flow disturbance index calculation unit 31 obtains the flowdisturbance index by calculating the index numerically from themorphology of the wall shear stress vectors. The flow disturbance indexis a numerical index that indicates the degree of alignment of the wallshear stress vector at a mesh with the surrounding wall shear stressvectors. In other words, the flow disturbance index is obtained bycalculating each angle θ between the wall shear stress vector of a meshtargeted for obtaining the flow disturbance index (the “targeted mesh”,hereinafter) and the wall shear stress vector of another mesh adjacentto the targeted mesh.

FIG. 25 illustrates an example of the relationship among the shearstress vector at an area element G (which is shown as a point forillustrative purpose) and the shear stress vectors at surrounding eightarea elements. In this example, the magnitudes of the shear stressvectors are not relevant but the directions, and hence they areexpressed as unit vectors to extract the directions only. Although,strictly speaking, the area elements form a three-dimensionalconfiguration, adjacent elements are very close and hence may be treatedas a two-dimensional configuration. In other words, each wall shearstress vector is projected onto a two-dimensional plane for processing.FIG. 25 illustrates a mapping of the area element G and its surroundingarea elements onto the two-dimensional coordinate system.

In the embodiment of the present invention, the divergence (“div”,hereinafter) and the rotation (“rot”, hereinafter) operations of thevector analysis are calculated for a targeted mesh in order to obtainnumerical values of the morphology of wall shear stress vectors.

That is, the components of the vector field τ (i.e., the shear stressvector) of a mesh in a three-dimensional space may be expressed as thecomponents at a point G(x, y) which is mapped into the two-dimensionalorthogonal coordinate system (x, y), which is given by the followingequation.τ(G)=(τx(x,y),τy(x,y))

Whence the “scalar field div τ”, which is called the “divergence of thevector field τ” is defined by the following equation:divτ=∂τx/∂x+δτy/∂y

Similarly, the “scalar field rot τ”, which is called the “rotation ofthe vector field τ” is defined by the following equation:rotτ=∂τy/∂x−∂τx/∂y

FIG. 26 depicts the relationship between the morphology of the wallshear stress vectors and the values of the aforementioned “divergence(div)” and “rotation (rot).” The morphology of the wall shear stressvectors has four categories: 1) parallel, 2) confluent, 3) rotational,and 4) divergent.

For the parallel, (div, rot)=(0, 0), for the confluent, (div,rot)=(negative value, 0), for the rotational, (div, rot)=(0, positive ornegative value), for the divergent, (div, rot)=(positive value, 0). Thedegree of confluent and divergent types can be quantified by thediv-value. That is, for the confluent type, if its negative valueincreases in the negative direction, the degree of confluence alsoincreases; and for the divergent type, if its positive value increasesin the positive direction, the degree of divergence also increase. Forthe rotational type, depending on the direction of rotation, both thepositive and the negative values appear but their absolute values may bea numerical parameter. If the flow disturbance index is defined by thevector quantity D=(div, rot), the magnitude may be used as the flowdisturbance index, i.e., as the flow disturbance becomes smaller, thewall shear stress vector tends to align along with other shear stressvectors at surrounding meshes (becoming closer to the parallel type).

If there is a flow disturbance index, its magnitude (as compared withthe threshold value) may be used to determine whether the blood flow ismalignant or benign, and furthermore, comparing the numerical value ofdiv with that of rot, the blood flow may be categorized to theconfluent, the rotational, and or divergent type, which may be used todetermine whether the aneurysmal wall is in a type of eitheratherosclerosis or wall thinning.

FIG. 27 shows a map of the numerical values of div and rot. Namely, thisfigure shows the flow disturbance index (div, rot) for a typical exampleof the shear stress vector. Here, the typical example is an idealmathematical pattern but not constructed from a set of experimentaldata. As described above, the magnitude of the shear stress vector isconverted to a unit vector having the norm one, and thus the flowdisturbance index is already normalized, which makes comparison amongdifferent patients possible. In other words, the embodiment of thepresent invention is capable of obtaining the index that may beevaluated as the absolute value of the flow disturbance index describedabove.

This embodiment of the present invention may combining the flowdisturbance index with the pressure on the targeted mesh as the weightcoefficient to make the flow disturbance index for accuratelydetermining the damage to the targeted blood vessel caused by the bloodflow pressurizing the vascular wall. This embodiment uses the normalizedpressure, i.e., the pressure index even when the pressure is used. Thisembodiment calculates the pressure index by each pressure divided by themean pressure in the lump. (The calculation is a multiplication in thiscase).

By the above argument, in a case where, for example, the divergence typeof the shear stress vectors is formed by the blood flow collision,increase of the local wall pressure may be observed from the collisionof the main flow but increase of the wall pressure may not be observedfrom the collision of the secondary flow separated from the main flow.In such a case, combining the morphology of the shear stress vectorswith pressure may refine the estimation, and in particular effectivelyestimate a thinning part of cerebral aneurysm. In other words, there areseveral methods for indexing the pressure, and hence the method foroverlaying the index with the flow disturbance which is calculated fromthe shear stress vector may take multiplication, division, or the powerlaw, and multiple methods are possible.

(Determination Unit)

The determination unit 32 determines if the flow at each mesh ismalignant or benign according to the flow disturbance index of each meshwhich is calculated by the flow disturbance index calculation unit 32.The conditions of the wall shear stress vector are: parallel to thesurrounding wall stress vectors, confluent to the directions of thesurrounding wall shear stress vectors, rotational along with thesurrounding shear stress vectors, or divergent from the directions ofthe surrounding wall shear stress vectors. If the wall shear stressvector at a mesh is in the parallel condition, the blood flowcharacteristics at the mesh is determined to be benign whereas if theblood flow characteristics at a mesh is confluent, rotational, ordivergent, the blood flow characteristics is malignant (not a benignflow) at the mesh.

Furthermore, the value of flow disturbance index in a malignant flow maybe used to evaluate the degree of risk. The embodiment of the presentinvention estimates that the risk is higher when the value of flowdisturbance index increases positively or negatively. Here the indexused as the threshold value is determined in such a way that theinventors of the present invention trace the time variation of the wallshear stress vectors in a cerebral aneurysm of a patient and determinethe threshold value empirically based on the correlation between thewall shear stress vectors and the actual vascular tissue of the cerebralaneurysm sampled from the patient, but the value may be changed in somecase. The threshold value may further be set stepwise and the conditionof the wall shear stress vector is set in several steps in order todetermine the degree of the benign flow and/or the malignant flow.

As disclosed above, the embodiment of the present invention maycategorize the condition of the vascular wall thickness (i.e., thelesion tendency) according to the state of the wall shear stress vector.If the wall shear stress vector is parallel, the wall thickness is at anormal level. If the wall shear stress vector is confluent orrotational, there is a tendency where blood cells and protein in bloodplasma are easily deposited, and the blood vessel turns to be anatherosclerosis type and increases the wall thickness. Furthermore, ifthe wall shear stress vector is divergent, it is a wall thinning typewhere damage and reproduction fault of endothelial cells cause atendency in which blood cells infiltrate, proliferate, and migrate intothe blood vessel, degrading the mechanical strength of the vascularwall, and as a result, decreasing the wall thickness around the lesion.FIG. 28 is a schematic diagram that shows the concept of theatherosclerosis-type and wall-thinning-type lesion.

FIG. 29 shows the user graphic interface 17 that displays the result ofthe blood flow characteristics determination unit 13 (the vectoroperation unit 30, the index calculation unit 31, and the determinationunit 32). As described previously, a user pushes the <Load> button ofthe interface 17 to read the analytical data as the input. The user thenselects the items to be displayed, from <Streamline> 61 to <Flowdisturbance index> 70 to complete the display layout of the interface.The user also may select parameters of blood vessel resistance:<Pressure ratio>, <Pressure loss coefficient>, and <Energy loss>. Fordisplaying the parameters, the user determines the starting and theending points for the central line of the blood vessel, and then thesystem automatically sets the volume of test and executes variouscalculations. As a result, the user interface 17 displays the result ofthe determination.

FIGS. 30A to D enlarge an example of determination. Referring to thesefigures, the effectiveness and the superiority of the <Flow disturbanceindex> are explained hereinafter.

The system displays the wall shear stress, the pressure, and the flowdisturbance index, each of which is normalized with the correspondingmaximum value on the aneurysm wall. On the display, a thinner colorindicates a larger value while a thicker color means a smaller value.For illustrative purpose, the wall shear stress (FIG. 30A) has threewall-thinning parts (P1, 2, and 3) which are identified by observing theaneurysmal wall during a surgery and analyzing the wall thickness.Because at the part P1, the wall shear stress is low while at the partP2 it is high, there is no common characteristics over the threewall-thinning parts. On the other hand, the wall shear stress vector(FIG. 30B) visualizes that the wall shear stress vectors are in thetendency of “divergent” at the 3 locations. In addition, at thelocations, FIG. 30C indicates that the pressure is also high. This meansthat the blood flow impinges with the aneurysm wall. Calculation of theflow disturbance index (divergent) reveals particularly higher values ofthe flow disturbance index (divergent) at the three locations of thinnerwalls as shown in FIG. 30D. In this example, the location in black hasthe flow disturbance index 0 (parallel, i.e., a benign flow), thelocation in grey has the flow disturbance index 1 (divergent, i.e., amalignant flow), and the location in white has the flow disturbanceindex 2 (divergent, i.e., a malignant flow).

In other words, there is a correlation between the thinner part and theflow disturbance index (divergent), and it is possible to determine thethinning part of an aneurysmal wall of a patient by applying thedetermination of the flow disturbance index (divergent) prior tosurgery.

As disclosed above, the determination unit of this system is capable ofdetermining whether the blood flow characteristics at each mesh ismalignant or benign based on the flow disturbance index, and the userinterface may visualize the result. In addition to the determinationresult, the blood flow characteristics (including the streamline, thefluid velocity, and the pressure) at each mesh obtained by the fluidanalysis unit is also displayed visually. The type and mode of displayeddata is not particularly limited, and, for example, it is possible tovisually recognize a region of high malignant flow density and otherregions in a patient's cerebral aneurysm by colorizing begin andmalignant flows at each mesh on the surface of a three-dimensional imageof the cerebral aneurysm produced from three-dimensional image data ofthe cerebral aneurysm that are produced by the vascular shape extractiondevice.

The flow disturbance index and the determination result of blood flowcharacteristics are stored in the simulation DB 16, as the items 74 and75 in FIG. 1. The result of determination is preferably stored so thatthe position (and the value) of a malignant flow is related to the valueof the flow disturbance index.

In the flow disturbance index calculation unit 31, the time dependenceof the flow disturbance index at each mesh may be also obtained as theflow disturbance index. That is, after calculating the flow disturbanceindex, the dynamical change of the flow disturbance index is calculatedby using the time average of the flow disturbance index and itsvariation, or the time-series data, the derivative, or the frequencyevaluation by using the Fourier transform. In this case, thecharacteristics determination means compares the calculated time changewith the pre-determined threshold vale to determine if the flow isbenign or malignant. In other words, if the time variation is smallerthan the pre-determined threshold value, the blood flow at a mesh isbenign, and on the other hand, if the time variation is larger than thepre-determined threshold value, the blood flow at the mesh is malignant.The threshold value is empirically determined based on the frequency ofthe heart pulsatile rate. The reason for this criterion refers toresearches which discover that the shear stress on the vascular wall ofcerebral aneurysm destroys vascular endothelial cells if the stressexerts at a frequency higher than the heart pulsatile rate.

The embodiment of the present invention discloses a system thatdetermines the probability of rupture of cerebral aneurysms; however,the present invention is not limited to the aneurysm but also can beapplied for other diseases in terms of determining the possibleappearance of lesion in other blood vessels and its potential growth.

Furthermore, the vector operation unit may be configured as a singlemathematical operation instrument that has the required functions. Themathematical operation instrument acquires the blood flow and thepressure at each unit area of the target vascular site, and calculatesthe wall shear stress vector on unit area of the vascular wall toproduce output data of the wall shear stress vector, which may bedisplayed through the interface 17.

(Application to a Surgery Skill Evaluation System)

The surgical simulation described by the embodiment of the presentinvention may also be applied to the following surgical skill evaluationsystem.

For example, a user who conducted a vascular anastomosis operation usinga blood vessel simulation model may process the DICOM format data of theblood vessel simulation model on which vascular anastomosis is operatedby uploading the data to the sever 3 of this system. The upload routinemay be also performed by applying another means such as the e-mailcommunication.

In this case, the blood flow analysis for a vascular anastomosis modelis carried out but at the same time, it is preferable for a user itselfto edit the morphology of the anastomotic part in order to conduct asimulation to investigate the procedure of vascular anastomosis or theloss of energy due to the surgery for validating the surgical technique.Therefore, in this case, in addition to the configuration of theembodiment, the system needs to have a unit for calculating the energyloss.

For this purpose, as shown in FIG. 31, in addition to the fluid analysisunit 12, the program storage unit of this system has an energy losscalculation unit 77, vascular shape modification unit 36, and a surgicalskill evaluation unit 78.

The energy loss calculation unit computes the energy of the blood flowat the inlet and the outlet of the model under investigation and theenergy loss by using the state quantities that the fluid analysis unitcalculated. The energy loss is then converted to the anastomoticstenosis rate (or the degree of stenosis) by normalizing it for thecross-section and the length of the blood vessel. The vascular shapemodification unit 36 uses the configuration of the shape modificationunit 36 in order to check which part of the internal shape of theanastomotic part needs to be altered for obtaining more effect on theblood flow score. The surgical skill evaluation unit 78 conducts thefollowing evaluations based on the energy loss (or the anastomoticstenosis rate (the degree of stenosis)).

For evaluating the surgical skill during a course of training thevascular anastomosis operation, re-establishing a smooth blood flow isimportant. “Smooth” means there is no morphological existence ofstenosis portion in the anastomotic lumen. A stenosis portion in theanastomotic lumen causes loss of energy. Hence in training the vascularanastomosis operation, it is ideal to perform anastomosis withoutstenosis in the anastomotic lumen. In training the vascular anastomosisoperation, the stenosis is considered to be a lesion claimed above. Thatis, unexperienced surgical skill causes the stenosis in the anastomoticlumen, bringing a circumstance where the post-surgical blood flow haslarge energy loss.

The surgical simulation program possibly evaluates how to improve thestenosis by interpreting it as a lesion in the aforementioned embodimentof the present invention. For example, a user may arbitrarily edit themorphology of lesion, i.e., the morphology of stenosis (by using thevascular shape editorial functions including enlargement, reduction, anddeletion) to investigate the cause and effect between the blood flow andthe surgical operation. Therefore, in this example, the evaluation unitis configured to use an interface similar to the aforementionedembodiment to show the relationships between the surgical skill and thelumen morphology, and the lumen morphology and the blood flow promptlyand intuitively on a computer display.

A vascular anastomosis operation using an automatic anatomic instrumentand conventional suture consequently produces different anastomosislumen. For example, an automatic anatomic instrument makes a T-shapedanatomic junction, and the anatomic cross-section is close to a circle.Thus, by enlarging or reducing the diameter of the anatomiccross-section, it is possible to simulate the result of an anastomosisoperation.

It would be expected that by editing the anatomic lumen, a simulation ofremoving part that does not affect the post-surgical blood flow may beconducted to design a new anatomic operation and a new clinicaldiscovery.

In addition, the configuration of the present invention is not limitedto the examples depicted by the figures herein, and variousmodifications may be attainable within the scope of the presentinvention.

What is claimed is:
 1. A computer-based system for determiningpatient-specific vascular information, the system comprising at leastone computer configured to: store template data containing names of aprincipal vascular element and other vascular elements in a vascularportion of a patient, which defines relative positional relationshipsamong the principal vascular element and the other vascular elements;receive first three dimensional data representing a shape of thevascular portion of the patient, the three dimensional data beingsuitable for simulations using computational fluid dynamics (CFD);determine, from the first three dimensional data, a cross-sectional areaof each of vascular elements in the vascular portion of the patient, andidentify a vascular element with a largest median value of the area asthe principal vascular element; and label names to the vascular elementsin the first three dimensional data, by applying the template data,based on the relative positional relationships with the principalvascular element.
 2. The system of claim 1, wherein, the template dataincludes a set of mesh detail levels, each mesh detail level beingassociated with a respective name of a vascular element, the at leastone computer is further configured to: conduct a CFD simulation usingthe first three dimensional data by varying the mesh detail levelsaccording to each vascular element based on the labeled name of thevascular element.
 3. The system of claim 2, the system being furtherconfigured to: receive an input from a user including a choice from aplurality of surgical treatments for a target site on the vascularportion, each of the surgical treatments being associated with a set ofinstructions to modify the first three dimensional data for the surgicaltreatment, modify the first three dimensional data according to theinstructions associated with the surgical treatment chosen by the user,thereby outputting second three dimensional data representing a shape ofthe vascular portion of the patient in a state after said surgicaltreatment chosen by the user is applied to the target site, and receiveand display, for planning a suitable surgical treatment for the patient,a result of a computational fluid dynamics (CFD) simulation on thesecond three dimensional data by varying the mesh detail levelsaccording to each vascular element based on the labeled name of thevascular element.
 4. The system of claim 3, the computer system beingfurther configured to: display the first three dimensional data, andreceive an input from the user, on the displayed first dimensional data,to specify the target site on the vascular portion.
 5. The system ofclaim 3, the computer system being further configured to: receive aresult of a CFD simulation on the first three dimensional data, anddisplay the results of the CFD simulations performed on the first andsecond three dimensional data in a manner that enables comparisons. 6.The system of claim 3, wherein said surgical treatments include coilembolization, and the set of instructions to modify the first threedimensional data for coil embolization comprises an instruction to placea porous structure on a part of the three-dimensional data at the targetsite on the vascular portion.
 7. The system of claim 6, the computersystem being further configured to adjust a coil filling ratio with anaperture ratio of the porous structure.
 8. The system of claim 3,wherein, the surgical treatments include clipping, the set ofinstructions to modify the first three dimensional data for clippingcomprises an instruction to remove one or more polygons which constitutea surface of a part of the first three dimensional data at the targetsite on the vascular portion, and an instruction to regenerate theremoved surface with one or more different polygons for simulating astate of blocking the part of the three dimensional data.
 9. The systemof claim 3, wherein, the surgical treatments include stent implantation,the set of instructions to modify the first three dimensional data forstent implantation comprises an instruction to modify an uneven surfaceon a part of the target site on the vascular portion by moving ordistorting one or more polygons which configure the uneven surface inthe first three dimensional data for simulating a state of controllingblood flow by the implantation of a stent.
 10. The system of claim 3,wherein, the surgical treatments include flow-diverting stentimplantation, the set of instructions to modify the first threedimensional data for the flow-diverting stent implantation comprising aninstruction for defining a lattice structured object on a part of thetarget site on the vascular portion for simulating a restricted bloodflow by implanting a flow-diverting stent.
 11. The system of claim 10,wherein, the set of instructions to modify the first three dimensionaldata for the flow-diverting stent implantation further comprises aninstruction for adjusting a pore density with an aperture ratio of thelattice structured object.
 12. The system of claim 3, wherein the resultof the CFD simulation includes information relating an energy loss ofblood flow at the vascular portion.
 13. The system of claim 2, whereinthe result of the CFD simulation includes information relating tovascular wall vulnerability characteristics at each computational meshon an inner surface of the vascular portion of the patient.
 14. Thesystem of claim 13, wherein, the information relating to the vascularwall vulnerability characteristics includes a disturbance in blood flowat and around each computational mesh on the inner surface of thevascular portion of the patient.
 15. The system of claim 14, thecomputer being further configured to determine a disturbance based on atleast a relative relationship among directions of wall shear stressvectors at and around each computational mesh on the inner surface ofthe vascular portion of the patient.
 16. The system of claim 15, thecomputer being further configured to: determine if the relativerelationship among the directions of the shear stress vectors at andaround each computational mesh on the inner surface of the vascularportion of the patient is “parallel”, “confluent”, “rotational”, or“divergent”, and determine the information relating to the vascular wallvulnerability characteristics to be benign (or non-malignant) if therelative relationship is “parallel”, otherwise malignant (ornon-benign), and display distinguishable symbols, each representingbenign or malignant respectively, the symbols being graphicallysuperposed on the three dimensional data.
 17. A method for determiningpatient-specific vascular information, the method comprising the stepsof: storing template data containing names of a principal vascularelement and other vascular elements in a vascular portion of a patient,which defines relative positional relationships among the principalvascular element and the other vascular elements; receiving first threedimensional data representing a shape of the vascular portion of thepatient, the three dimensional data being suitable for simulations usingcomputational fluid dynamics (CFD); determining, from the first threedimensional data, a cross-sectional area of each of vascular elements inthe vascular portion of the patient, and identify a vascular elementwith a largest median value of the area as the principal vascularelement; and labeling names to the vascular elements in the first threedimensional data, by applying the template data, based on the relativepositional relationships with the principal vascular element.
 18. Themethod of claim 17, wherein, the template data includes a set of meshdetail levels, each mesh detail level being associated with a respectivename of a vascular element, the method further comprises the step ofconducting a CFD simulation using the first three dimensional data byvarying the mesh detail levels according to each vascular element basedon the labeled name of the vascular element.
 19. The method of claim 18,further comprising the steps of: receiving an input from a userincluding a choice from a plurality of surgical treatments for a targetsite on the vascular portion, each of the surgical treatments beingassociated with a set of instructions to modify the first threedimensional data for the surgical treatment, modifying the first threedimensional data according to the instructions associated with thesurgical treatment chosen by the user, thereby outputting second threedimensional data representing a shape of the vascular portion of thepatient in a state after said surgical treatment chosen by the user isapplied to the target site, and receiving and displaying, for planning asuitable surgical treatment for the patient, a result of a computationalfluid dynamics (CFD) simulation on the second three dimensional data byvarying the mesh detail levels according to each vascular element basedon the labeled name of the vascular element.
 20. The method of claim 19,further comprising the steps of: displaying the first three dimensionaldata, and receiving an input from the user, on the displayed firstdimensional data, to specify the target site on the vascular portion.21. The method of claim 19, further comprising the steps of: receiving aresult of a CFD simulation on the first three dimensional data, anddisplaying the results of the CFD simulations performed on the first andsecond three dimensional data in a manner that enables comparisons. 22.The method of claim 19, wherein said surgical treatments include coilembolization, and the set of instructions to modify the first threedimensional data for coil embolization comprises an instruction to placea porous structure on a part of the three-dimensional data at the targetsite on the vascular portion.
 23. The method of claim 22, furthercomprising the step of adjusting a coil filling ratio with an apertureratio of the porous structure.
 24. The method of claim 19, wherein, thesurgical treatments include clipping, the set of instructions to modifythe first three dimensional data for clipping comprises an instructionto remove one or more polygons which constitute a surface of a part ofthe first three dimensional data at the target site on the vascularportion, and an instruction to regenerate the removed surface with oneor more different polygons for simulating a state of blocking the partof the three dimensional data.
 25. The method of claim 19, wherein, thesurgical treatments include stent implantation, the set of instructionsto modify the first three dimensional data for stent implantationcomprises an instruction to modify an uneven surface on a part of thetarget site on the vascular portion by moving or distorting one or morepolygons which configure the uneven surface in the first threedimensional data for simulating a state of controlling blood flow by theimplantation of a stent.
 26. The method of claim 19, wherein, thesurgical treatments include flow-diverting stent implantation, the setof instructions to modify the first three dimensional data for theflow-diverting stent implantation comprising an instruction for defininga lattice structured object on a part of the target site on the vascularportion for simulating a restricted blood flow by implanting aflow-diverting stent.
 27. The method of claim 26, wherein, the set ofinstructions to modify the first three dimensional data for theflow-diverting stent implantation further comprises an instruction foradjusting a pore density with an aperture ratio of the latticestructured object.
 28. The method of claim 19, wherein the result of theCFD simulation includes information relating an energy loss of bloodflow at the vascular portion.
 29. The method of claim 18, wherein theresult of the CFD simulation includes information relating to vascularwall vulnerability characteristics at each computational mesh on aninner surface of the vascular portion of the patient.
 30. The method ofclaim 29, wherein, the information relating to the vascular wallvulnerability characteristics includes a disturbance in blood flow atand around each computational mesh on the inner surface of the vascularportion of the patient.
 31. The method of claim 30, further comprisingthe step of determining a disturbance based on at least a relativerelationship among directions of wall shear stress vectors at and aroundeach computational mesh on the inner surface of the vascular portion ofthe patient.
 32. The method of claim 31, further comprising the stepsof: determining if the relative relationship among the directions of theshear stress vectors at and around each computational mesh on the innersurface of the vascular portion of the patient is “parallel”,“confluent”, “rotational”, or “divergent”, and determining theinformation relating to the vascular wall vulnerability characteristicsto be benign (or non-malignant) if the relative relationship is“parallel”, otherwise malignant (or non-benign), and displayingdistinguishable symbols, each representing benign or malignantrespectively, the symbols being graphically superposed on the threedimensional data.